We evaluate gsf on five standard action recognition benchmarks, Something Something [1]} (SS-V1 and SS-V2), Kinetics 400 [2]}, Diving48 [3]} and EPIC-Kitchens-100 [4]}. Something-V1 and Something-V2 consists of fine-grained object manipulation actions comprising of 174 categories. Something-V1 consists of  100K videos while Something-V2 is an updated version of Something-V1 with  220K videos. Kinetics 400 is a large scale dataset consisting of 400 action categories with at least 400 clips per action class. Diving48 dataset contains around 18K videos with 48 fine-grained diving categories. EPIC-Kitchens-100 is the largest egocentric action recognition dataset with  90K video clips. Each clip in the dataset is labelled with a verb and noun class from a possible set of 97 verb classes and 300 noun classes. The verb and noun category pairs are combined to form an action class.
